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Investigation of the molecular link between common variable immunodeficiency and gastric cancer by integrated bioinformatics analysis

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2021
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Abstract (EN)

Common Variable Immunodeficiency (CVID) is the most common type among primary immunodeficiencies and increasing evidence shows that CVID patients are more predisposed to gastric cancer than the healthy population. Efforts to identify unknown shared molecular mechanisms underlying both diseases may have significant public health implications by stratifying individuals that have risks for CVID-related gastric cancer and developing new translational approaches. Thus, we aimed to define candidate common molecular biomarkers and molecular pathways that may have a role in the relationship between CVID and gastric cancer by bioinformatics analysis. Data sets used in the study were retrieved from the NCBI-GEO database and differentially expressed genes (DEG) analysis was performed using 'R' software. NetworkAnalyst and Ingenuity Pathway Analysis (IPA) software were used for functional pathway enrichment analyzes of common DEGs. The hub genes were identified and visualized by Cytoscape software. Common miRNAs targeting hub genes were also investigated by the mirDIP database. Our results revealed many common DEGs and molecular pathways that may contribute to the development of both diseases. Also, we prioritized three hub genes (MZB1, GBP1, CXCL10) and three microRNAs (hsa-miR-3659, hsa-miR-4483, hsa-miR-6790-5p) suggesting a common role in the molecular etiology of the two diseases. In addition, IPA analysis suggests the involvement of the identified hub genes in pathways such as "apoptosis", "death of immune cells" and "systemic autoimmune syndrome". Our results highlight promising in silico evidence for candidate common molecular mechanisms for CVID and gastric cancer, which should be confirmed by in vivo and/or in vitro studies.

Author

Berna Ayar

How to Cite

Berna Ayar (Master Thesis). Investigation of the molecular link between common variable immunodeficiency and gastric cancer by integrated bioinformatics analysis, 2021, Bursa Uludağ Üni̇versi̇ty.

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